Engineering Grant Seeks to Predict Falls – and How to Stop Them

More than 2.8 million older Americans visit emergency rooms for fall-related injuries each year, but UCF Assistant Professor Helen Huang hopes those numbers can be reduced with the help of a new $1.5 million research grant she received to find new approaches for predicting fall risk and creating balance-training programs.

Huang secured the National Institutes of Health R01 Award in her second year as an assistant professor in UCF’s Department of Mechanical & Aerospace Engineering. The five-year grant awarded in August by the National Institute on Aging will look at “Adaptation of brain and body responses to perturbations during gait in young and older adults.”

To work towards brain-based gait rehabilitation and fall interventions, researchers must first determine the brain processes involved in balance control during walking, and recovery from losses of balance in young and older adults. Huang’s research involves collecting brain-wave and muscle-activity data to understand how people maintain their balance and adapt their movement patterns to disruptions during walking and exercise.

In addition to preventing the debilitation of hip fractures and head injuries, the findings would help reduce the economic burden of falls among older adults. The medical costs associated with falls in the United States total about $31 billion each year, according to the National Center for Injury Prevention and Control.

Tests will be carried out on a specially fitted treadmill that has two belts to walk on, one for each leg. The belt speeds can be run independently so one belt can go faster than the other.

“We use this feature to suddenly slow down or speed up a belt for a fraction of a second to create a small slip backwards or trip forwards,” Huang said. “The treadmill can also shift side to side. With this feature, we can create a slip in the side-to-side direction.”

By applying changes on the treadmill, researchers can see how the subjects react and adapt their walking pattern.

The treadmill’s incline/decline also can be adjusted as people walk to create a rolling terrain and it also has a self-paced mode, which allows the machine to change its speed to match the person’s walking speed.

While walking on the treadmill, the subjects’ brain waves will be recorded using electroencephalography with electrodes placed on the scalp to measure electrical activity generated by neurons in the brain. The system has 128 electrodes and will process the data to identify the brain areas that are the primary sources of the electrical activity during walking and responding to the perturbations.

“We expect to find that both young and older adults can adapt to these perturbations but that older adults will adapt less,” Huang said. “We expect that subjects will use a combination of anticipating and reacting to the perturbations to maintain their balance.

“If we could identify who is more likely to fall, then we could develop preventative balance-training programs to help reduce their fall risk. Additionally, we hope to be able to use brain dynamics to help customize fall-training programs and interventions for each individual.”

Her co-investigator on the grant is Professor Carolynn Patten at the University of Florida. Also helping with the project will be Assistant Professor Ladda Thiamwong in the UCF College of Nursing and Assistant Professor Hsin-Hsiung Huang in the Statistics department, who were added co-investigators once the project began.

Huang, who has a Ph.D. in biomedical engineering from the University of Michigan, said this research meshes with her lifetime interest in movement and sports.

“I’ve played many sports throughout my life, and having a good sense of balance is beneficial. Unfortunately, I have really bad balance from repeated ankle sprains,” she said. “I seem to trip over imaginary lines and sprain my ankles on pea-sized pebbles.”

The study is looking for healthy volunteers 18-35 years old and 60-85 years old. Interested individuals can contact the team to conduct a brief interview about their overall health to determine eligibility. Interested individuals can email ucfbrainlab@gmail.com[1] to learn more about the project.